Instructions to use fairnlp/albert-cda with libraries, inference providers, notebooks, and local apps. Follow these links to get started.
- Libraries
- Transformers
How to use fairnlp/albert-cda with Transformers:
# Use a pipeline as a high-level helper from transformers import pipeline pipe = pipeline("feature-extraction", model="fairnlp/albert-cda")# pip install -U transformers accelerate # Load model directly from transformers import AutoTokenizer, AutoModel tokenizer = AutoTokenizer.from_pretrained("fairnlp/albert-cda") model = AutoModel.from_pretrained("fairnlp/albert-cda", device_map="auto") - Notebooks
- Google Colab
- Kaggle
Download special_tokens_map.json from fairnlp/albert-cda: direct link, hf CLI and curl.
- Browser
- Download file 286 Bytes
-
https://huggingface.co/fairnlp/albert-cda/resolve/main/special_tokens_map.json
- Command line
-
hf download hf://fairnlp/albert-cda/special_tokens_map.json
-
curl -L -o special_tokens_map.json https://huggingface.co/fairnlp/albert-cda/resolve/main/special_tokens_map.json
286 Bytes
| { | |
| "bos_token": "[CLS]", | |
| "cls_token": "[CLS]", | |
| "eos_token": "[SEP]", | |
| "mask_token": { | |
| "content": "[MASK]", | |
| "lstrip": true, | |
| "normalized": false, | |
| "rstrip": false, | |
| "single_word": false | |
| }, | |
| "pad_token": "<pad>", | |
| "sep_token": "[SEP]", | |
| "unk_token": "<unk>" | |
| } | |